This invention relates generally to magnetic resonance (MR) imaging (MRI) techniques. In particular, it relates to single-scan three-point Dixon methods for generating water/fat component images and, more particularly, to a post data-acquisition method for generating water/fat separated MR images wherein the relaxation contrasts are adjustable.
Magnetic Resonance Imaging (MRI) has become a widely accepted and commercially available technique for obtaining digitized visual images representing the internal structure of objects (such as the human body) having substantial populations of atomic nuclei that are susceptible to nuclear magnetic resonance (NMR) phenomena. In MRI nuclei in a body to be imaged are polarized by imposing a strong main magnetic field H0 on the nuclei. Selected nuclei are excited by imposing a radio frequency (RF) signal at a particular NMR frequency. By spatially distributing the localized magnetic fields, and then suitably analyzing the resulting RF responses from the nuclei, a map or image of relative NMR responses as a function of the location of the nuclei can be determined. Following a Fourier analysis, data representing the NMR responses in space can be displayed on a CRT.
As shown in FIG. 1, the NMR imaging system typically includes a magnet 10 to impose the static magnetic field, gradient coils 14 for imposing spatially distributed magnetic fields along three orthogonal coordinates, and RF coils 15 and 16 to transmit and receive RF signals to and from the selected nuclei. The NMR signal received by the coil 16 is provided to computer/image processor 19 which processes the data into an image displayed on display 24. The displayed image is composed of picture elements called xe2x80x9cpixelsxe2x80x9d, defined as the field of view (FOV) divided by the number of data elements (N). The intensity of a pixel is proportional to the NMR signal intensity of the contents of a corresponding volume element or xe2x80x9cvoxelxe2x80x9d of the object being imaged. The computer/processor 19 also controls the operation of RF coils 15 and 16 and gradient coils 14 through the RF amplifier/detector 21 and 22 and gradient amplifiers 20, respectively.
Only nuclei with odd number of protons and/or neutrons have a magnetic moment and thus are susceptible to NMR phenomena. In MRI, a strong static magnetic field is employed to align nuclei, generating a gross magnetization vector aligned in parallel to the main magnetic field at equilibrium. A second magnetic field, applied transverse to the first field as a single RF pulse, pumps energy into the nuclei, which causes the gross magnetization vector to flip by, for example, 90xc2x0. After this excitation, the nuclei precess and gradually relax back into alignment with the static field. As the nuclei precess and relax, they will induce a weak but detectable electrical energy in the surrounding coils that is known as free induction decay (FID). These FID signals (and/or magnetic gradient-refocused field echoes thereof), collectively referred to herein as MR signals, are then analyzed by signal processor 19 to produce images of the nuclei in space.
An operation whereby the various coils produces RF excitation pulses and gradient fields to result in and acquire an MR signal is called an MRI xe2x80x9cacquisition sequencexe2x80x9d. A graphical representation of an example MRI acquisition sequence used for three-dimensional (3-D) MRI is shown in FIG. 2. In this example, the particular timing of applied pulses and fields is known as a field-echo sequence since the MR signals appear as gradient-refocused field echoes. First, a gradient field, Gslice, is superimposed along the main field to sensitize a slab of nuclei in the body to be imaged to a particular RF resonance frequency. An RF excitation field or nutation pulse, xcex8, is then applied at the particular frequency to tip the magnetization away from equilibrium. Thereafter, pulsed magnetic gradient fields of changing magnitudes, Gpe and Gslice, are used to phase encode the nuclei by inducing a temporary frequency difference, and hence phase differences, between nuclei in different locations along a specific direction within the slab. At the same time, another pulsed magnetic gradient field, Gro, is applied perpendicular to the direction of Gpe, in a readout (ro) direction that first de-phases and then rephases the precessing nucleixe2x80x94which results in producing a field-echo MR signal represented in FIG. 2 as S. The time from the center of nutating pulse, xcex8, to the center of the field-echo MR signal is designated as the echo time, TE, and the entire pulse sequence duration is designated as TR.
Essentially, the applied gradient field, Gro, frequency encodes the selected slab of nuclei in the readout direction. The resultant MR signal, S, (also called xe2x80x9craw dataxe2x80x9d or xe2x80x9ck-space dataxe2x80x9d) is then read and analyzed by Fourier analysis. A frequency domain plot of that analysis is then scaled to render information about the nuclei population in Fourier space (also referred to as the image domain), which corresponds to an X-Y-Z position.
A magnetization vector can be decomposed into longitudinal and transverse components in reference to the main B0 field. Conventionally, the longitudinal component is defined as parallel to the B0 field and the transverse component is defined as perpendicular to B0. Once the magnetic vectors are disturbed from their equilibrium, processes known as xe2x80x9crelaxationxe2x80x9d cause the longitudinal component to recover to an equilibrium magnitude, M0, in alignment with the background B0 field, and the transverse component to decay. These relaxation processes are respectively termed the xe2x80x9cspin-lattice relaxationxe2x80x9d and the xe2x80x9cspin-spin relaxationxe2x80x9d and are characterized by exponentials whose defined time constants are labeled as T1 and T2, respectively. In addition to spin-spin (T2) relaxation, inhomogeneities in magnetic field cause the transverse component to further decay. An xe2x80x9capparent relaxationxe2x80x9d time constant, T2, is therefore defined as characterizing transverse signal decay due to both spin-spin relaxation and the presence of B0 field inhomogeneities.
The NMR frequency and the main B0 field are related by the Larmor relationship. This relationship states that the angular frequency, xcfx890, of the precession of the nuclei is the product of the magnetic field, B0, and the so-called magnetogyric ratio, xcex3, a fundamental physical constant for each nuclear species:
xcfx890=B0xc2x7xcex3(1xe2x88x92"sgr")
where "sgr" is a shielding factor representing the chemical environment around the nuclei, commonly referred to as the xe2x80x9cchemical shift.xe2x80x9d
The RF spin-nutating pulse will, of course, tip more than one species of the target isotope in a particular area. After being tipped away from equilibrium, each species of nuclei will begin to precess at their own characteristic speed. The phase of the precessing nuclei species will gradually differ (de-phase) as a result of such parameters as the physical or chemical environment in which the nuclei are located. Nuclei in fat, for example, precess at a different rate than do nuclei in water due to the effects of chemical shift. In addition, inhomogeneities in the magnetic field also contribute to de-phasing of the nutated precessing nuclei.
Since hydrogen nuclei have a readily discernible NMR signal and are the most abundant isotope of the human body, human MRI primarily images the NMR signal from the hydrogen nuclei. Water and fat are the main tissue components containing hydrogen nuclei.
In addition to using the frequency information content of an MR signal to generate images, the phase of an MR signal in the frequency domain can be utilized to provide information indicative of some physical quantity. For example, depending on the type of pulse sequence used, the MR phase can be used to differentiate between water and fat. It can also represent a main B0 field inhomogeneity or can be proportional to the velocity of the moving spins.
I. Water and Fat Separation
Although MR images of both water and fat may contain the same or different diagnostic information, they often interfere with each other""s interpretation when overlapped in an MRI image, and thus make it difficult to properly interpret the composite MR image.
At high-magnetic-field strengths, the separation of water and fat images or suppression of one of these two components can be achieved using selective excitation or non-excitation approaches. At mid- or low-field strengths, approaches based on chemical shift selectivity become impractical, if not impossible. At all field strengths, the difficulties of water/fat image separation are further exacerbated when imhomogeneities are present in the magnetic field.
One group of techniques, known as xe2x80x9cThree-Point Dixonxe2x80x9d methods, have attractive features for mid- or low-field strength applications. These methods require three images to obtain enough information for water/fat separation with correction of the effect of B0 field inhomogeneities. The images can be acquired using spin-echo as well as field-echo sequences, in three separate scans, as described in xe2x80x9cThree-Point Dixon Technique for True-Water/fat Decompositions with B0 Inhomogeneity Corrected,xe2x80x9d by Glover et al., Magnetic Resonance in Medicine 18, 371-383 (1991); in two scans, as described in xe2x80x9cSeparation of True Fat and Water Images by Correcting Magnetic Field Inhomogeneity In Situxe2x80x9d, by Yenng et al., Radiology 159, 783-786 (1986), or in a single scan, as described in xe2x80x9cTrue Water and Fat MR Imaging with Use of Multiple-Echo Acquisitionxe2x80x9d, by William et al., Radiology 173, 249-253 (1989) and xe2x80x9cSeparation of Water and Fat MR Images in a Single Scan at 0.35 T Using xe2x80x98Sandwichxe2x80x99 Echoes,xe2x80x9d by Zhang et al., JMRI 6, 909-917 (1996), all the above of which are incorporated herein by reference.
In accordance with the above Three-Point Dixon methods, acquisitions of the three images are controlled so that the phase difference between the water image information and the fat image information changes by xc2x1xcfx80 radians (180xc2x0) between the three images (i.e., Sxe2x88x92xcfx80, S0, and Sxcfx80). Data from the three images is then processed to remove the effects of magnetic field inhomogeneities and, ultimately, to generate separate water and fat images. In accordance with the method, magnetic field inhomogeneities are compensated by using information from two of the three images through a process of xe2x80x9cphase unwrapping.xe2x80x9d
Since the phase angle of a complex number is unambiguous only between xe2x88x92xcfx80 and xcfx80, the phase of an MRI signal cannot be unambiguously determined from its argument, and any phase values beyond xe2x88x92xcfx80 or xcfx80 will be xe2x80x9cwrappedxe2x80x9d back around into values between xe2x88x92xcfx80 and xcfx80. In this context, phase unwrapping is the process of determining the absolute phase of a complex signal given the measurement of its principal phase value. (Two of such processes are outlined further below).
Ignoring the effects of relaxation, the NMR signal data comprising the three Dixon images can be described by:
xe2x80x83Sxe2x88x92xcfx80=(Wxe2x88x92Fexe2x88x92ixcexa8di0)exe2x88x92i(xcfx860xe2x88x92xcfx86)
S0=(W+Fexe2x88x92ixcexa80)exe2x88x92ixcfx860
Sxcfx80=(Wxe2x88x92Fexe2x88x92ixcexa80)exe2x88x92i(xcfx860+xcfx86)
where W and F represent water and fat signals, respectively; xcexa80 is the phase difference between water and fat observed in S0; xcfx860 is the phase in S0 due to field inhomogeneities and other system sources; xcfx86 is phase change between the successive echoes induced by field inhomogeneities.
To correct for field inhomogeneities, the compensation angle, xcfx86, is determined from Sxe2x88x92xcfx80 and Sxcfx80 by the process of phase unwrapping in accordance with the following relationship:
xcfx86=xc2xd unwrap {arg(Sxe2x88x92xcfx80xc2x7S*xcfx80)}
where arg ( ) produces the phase angle of a complex number, and * represents complex conjugation.
Water-only images, W, and fat-only images, F, can then be reconstructed in accordance with the following two relationships:
W=So+0.5Sxcfx80e+ixcfx86+0.5Sxe2x88x92xcfx80exe2x88x92ixcfx86
F=Soxe2x88x920.5Sxcfx80eixcfx86xe2x88x920.5Sxe2x88x92xcfx80exe2x88x92ixcfx86
One can also rely on just one image, S, in which the water and fat signals have a difference in phase by 180xc2x0. Though water and fat signals are not truly separated in such cases, image pixels can be sorted in accordance to whether they are dominated by water or by fat by applying the following relationships:
S=(Wxe2x88x92F)exe2x88x92ixcfx86
xcfx86=xe2x88x92xc2xd unwrap{arg(S2)}
Iwater-pixel=|S|+Seixcfx86
Ifat-pixel=|S|xe2x88x92Seixcfx86
where Iwater-pixel and Ifat-pixel represent water-dominant and fat-dominant pixels, respectively.
II. Phase Unwrapping
Preferred algorithms for phase unwrapping as implemented in the present invention involve a combination of modeling the static magnetic field using polynomial functions and a xe2x80x9cguidedxe2x80x9d phase unwrapping by xe2x80x9cregion-growingxe2x80x9d.
i. Polynomial Field Modeling
The magnetic field is modeled using a polynomial function:       B    ⁢          (              x        ,        y            )        =            ∑              n        =        1            3        ⁢          "AutoLeftMatch"                                    [                          "AutoLeftMatch"                                                a                  n                                (                                  x                  -                                      x                    o                                                  "AutoRightMatch"                            "AutoRightMatch"                        )                    n                +                                            "AutoLeftMatch"                                                b                  n                                ⁢                                  (                                      y                    -                                          y                      o                                                        )                                            "AutoRightMatch"                        n                    ]                +                  c          o                    
To find the coefficients an and bn, partial spatial derivatives of the phase value xcfx86 are calculated and fit to polynomial functions as follows:                     ∂                  φ          ⁢                      (                          x              ,              y                        )                                      ∂        x              =                            p          3                ⁢                  x          2                    +                        p          2                ⁢        x            +              p        1                                ∂                  φ          ⁢                      (                          x              ,              y                        )                                      ∂        y              =                            q          3                ⁢                  y          2                    +                        q          2                ⁢        y            +              q        1            
Fitting is performed using a weighted least-square with the weighting factors determined according to:       w    ⁢          (              x        ,        y            )        =            S      ⁢              (                  x          ,          y                )                    S      max      
where S(x,y) is the pixel value in the in-phase image and Smax is the maximum of that image.
Using pn and qn, an and bn are calculated according to the following equations:
a1=p1+2p2xo+p3xo2
a2=xc2xdp2+p3xo
a3=⅓p3
b1=q1+2q2yo+q3yo2
b2=xc2xdq2+q3yo
b3=⅓q3
ii. Phase Unwrapping by Guided Region Growing
The phase image is unwrapped using a guided region-growing algorithm as follows:
(a) A pixel in the image is chosen as the subseed for unwrapping and the measured phase value is assigned to the final phase value used for water and fat image reconstruction.
xcfx86f(x0,y0)=xcfx86(x0,y0)
(b) The subseed is selected so that all pixels in a 6xc3x976 region centered at the subseed have sufficient signal strength. The four immediately neighboring pixels of the subseed are first unwrapped by comparing the phase values to the subseed value. If the difference is larger than a predetermined threshold, a 2xcfx80 unwrapping is executed:
xcfx86f=xcfx86+sign(xcex94xcfx86)x2xcfx80
xcex94xcfx86=xcfx86xe2x88x92xcfx86(x0,y0)
where:
(c) A 3xc3x973 pixel region centered at the subseed is then built based on the five already-determined pixels. A 2xcfx80 phase unwrapping is executed whenever the phase difference between a pixel and its already-unwrapped, immediate neighboring pixel is larger than the threshold.
(d) The 3xc3x973 region is then expanded to 4xc3x974 region with a three-pixel prediction:
xcfx86p=⅓(xcfx86fxe2x88x923+xcfx86fxe2x88x922+xcfx86fxe2x88x921)+⅓(3xcex94xcfx86xe2x88x921+2xcex94xcfx86xe2x88x922+xcex94xcfx86xe2x88x923)
where xcfx86p is the predicted phase value of a pixel; xcfx86fxe2x88x92i(i=1, 2, 3) are the phase values of the already unwrapped first (i=1), second (i=2), and third (i=3) neighboring pixels; xcex94xcfx86xe2x88x92i are the phase spatial derivatives of the already-unwrapped, neighboring pixel along the direction of the prediction.
Unwrapping is executed if xcex94xcfx86=xcfx86xe2x88x92xcfx86p is larger than the threshold.
(e) Continuing from the 4xc3x974 seed region, a four column by four rows xe2x80x9ccrossxe2x80x9d region is built using a four-pixel prediction:
xcfx86p=xc2xc(xcfx86fxe2x88x924+xcfx86fxe2x88x923+xcfx86fxe2x88x922+xcfx86fxe2x88x921)+xc2xc(4xcex94xcfx86fxe2x88x921+3xcex94xcfx86fxe2x88x922+2xcex94xcfx86fxe2x88x923+xcex94xcfx86fxe2x88x924)
(f) Using the cross, the four quadrants of the image are unwrapped using the same 4-pixel prediction approach, but in two directions. Unwrapping is executed when both directions show the same execution for unwrapping. In other situations, the average of the predicted values is used. When the pixel value is below the intensity threshold, the phase value is again set to the predicted average value.
In the past, water/fat separation at low and mid-level field intensities have been most successfully achieved using the above discussed multiple-point Dixon methods. Moreover, as described above, a single-scan three-point Dixon method (with the water and fat signals evolving a phase difference of xcfx80 during the inter-echo time xcex94TE) can acquire three consecutive NMR echo signals after only a single excitation pulsexe2x80x94resulting in a significant reduction in scanning-time. However, in addition to the phase information used to separate water/fat with correction of Bo inhomogenities, the three-point Dixon echo signals contain information about spin relaxation decay. Accordingly, the present invention exploits such information after data acquisition to provide water/fat separated images with adjustable relaxation contrasts.
The present invention is a post data-acquisition MRI technique for generating water/fat separated MR images wherein the resultant relaxation image contrast in water-only or fat-only images is adjustable under operator control by selecting a value for the contrast echo time (newTE) used in constructing the water-only or fat-only images.
In accordance with the present invention, single-scan three-point Dixon imaging is used to obtain the NMR raw signal data. Basically, in three-point Dixon imaging, a slice-selective excitation pulse is followed by the acquisition of three separate gradient-refocused signal-echoes. Each signal echo is acquired by controlling the timing and polarity of an applied read-out gradient. The time (xcex94TE) between the signal-echoes (S1, S2, S3) is selected according to the chemical-shift difference between water and fat signals so that the two signals develop between them an angular difference of xcfx80 radians (180xc2x0) during the inter-echo time.
After Fourier conversion of the raw data (k-space data) to complex frequency-domain data, also called xe2x80x9cimage-domainxe2x80x9d data, background magnetic field inhomogeneities are compensated by obtaining the compensation phase from the S1 and S3 signal-echoes using a guided region-growing phase unwrapping technique. Next, the effects of T2 relaxation or T*2 relaxation are measured from the signal data. The acquired image data are then corrected according to the relaxation measurements based on an operator-selected new contrast TE (newTE) value. Water and fat signals are finally separated from the corrected image data, producing water-only or fat-only images with enhanced relaxation contrast.